Empirical Loss Landscape Analysis of Neural Network Activation Functions-Reference-Cited by-同舟云学术

Empirical Loss Landscape Analysis of Neural Network Activation Functions

Published:2023-07-15 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the Companion Conference on Genetic and Evolutionary Computation
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Author:

Bosman Anna Sergeevna¹^ORCID,Engelbrecht Andries²³^ORCID,Helbig Marde⁴^ORCID

Affiliation:

1. Computer Science, University of Pretoria, Pretoria, Gauteng, South Africa

2. University of Stellenbosch, Stellenbosch, South Africa

3. Center for Applied Mathematics and Bioinformatics, Gulf University for Science and Technology, Kuwait City, Kuwait

4. School of Information and Communication Technology, Griffith University, Southport, Australia

Funder

National Research Foundation

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3583133.3596321

Reference35 articles.

1. Raman Arora , Amitabh Basu , Poorya Mianjy , and Anirbit Mukherjee . 2018 . Understanding deep neural networks with rectified linear units . In Proceedings of the International Conference on Learning Representations . Vancouver, Canada, 1--17. Raman Arora, Amitabh Basu, Poorya Mianjy, and Anirbit Mukherjee. 2018. Understanding deep neural networks with rectified linear units. In Proceedings of the International Conference on Learning Representations. Vancouver, Canada, 1--17.

2. Visualising basins of attraction for the cross-entropy and the squared error neural network loss functions

3. Search space boundaries in neural network error landscape analysis

4. Progressive gradient walk for neural network fitness landscape analysis

5. Loss Surface Modality of Feed-Forward Neural Network Architectures

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